How Leaders Can Use AI to Drive Growth and Innovation

In recent years, organizations have explored and argued and fretted over the potential impact and disruption of Artificial Intelligence (AI).

However, AI is no longer futuristic. It’s here now, and it’s taking shape in most industries.

Strategic leaders already use AI to enhance operations, innovate products, and to develop competitive advantage. This means we can already see what’s working (and what’s not) to reframe fears as opportunities.

In this article, we’ll examine how to enhance customer experience, innovation, and growth with AI, and we’ll explore why culture and leadership are critical to your success.

Where AI Is Driving Value in Business Today

Four of the biggest areas AI has the potential to transform business today include:

1. Operational Efficiency

AI can handle complicated logistics processes like warehouse automation and inventory management. This can simplify supply chain management and minimize costs, which can be transformational when margins are tight. [1]

However, only 19 percent of logistics companies in the U.K., U.S., and Germany are using AI (like the Internet of Things, location data, and sensor technology) for advanced-use cases. [1][2]

As such, there’s an opportunity here for companies in this sector to take advantage of extreme cost and time savings.

2. Customer Experience

Organizations in most sectors can enhance customer experience with chatbots, which offer a high level of personalization.

In 2023, AI chatbots could summarize data to generate responses to customer inquiries. Just two years later, AI agents have become far more advanced. They can now engage with customers and select actions to take following conversations.

These actions may include checking for fraud, processing payments, and completing shipping actions. [3]

3. Product and Service Innovation

Generative AI is becoming increasingly advanced. As a result, many organizations are leveraging this to improve their product or service prototypes. These organizations are bringing algorithms to their artistry to stay creative while improving productivity.

For example, film studios and music producers are developing soundtracks and impressively realistic visual effects at speed.

Meanwhile, education organizations are customizing their learning experiences to each user’s needs. Generative AI allows them to introduce adaptive content generation and provide real-time feedback. [4]

4. Decision Making and Forecasting

Many organizations are also using decision-intelligence AI to strategize for the future. For example, in the context of a supply chain, AI can predict and analyze sales volumes, inventory levels, transportation costs, and weather data.

From here, it can place orders at carefully selected quantities to meet demand without overspending. Organizations leveraging this AI can make the right purchasing decisions at exactly the right time. [5]

What Makes a Leader AI-Ready

You can adopt these four characteristics to prepare yourself for AI-ready leadership. To make the shift, focus on the following:

1. Be open-minded and forward-thinking. Your organization’s current practices may no longer serve it effectively. Embracing change by responding to evolving customer expectations and trialing new technologies can streamline operations while boosting return on investment.
2. Be willing to test, iterate, and learn fast. When used incorrectly, AI can hinder output. A 2024 study revealed that while 96 percent of C-suite leaders expected AI to boost productivity, it increased workloads for 77 percent of employees. [6] Whichever solution you invest in, iterating will be vital to improving productivity over time.
3. Become skilled at balancing innovation with governance. AI solutions often come with ethical concerns. These may include environmental, privacy, cybersecurity, and hiring bias risks. Leaders need to protect against these concerns while innovating, perhaps most notably by training team members to manage the risks.
4. Build teams that mix human insight and AI tools. AI may affect nearly 40 percent of employed roles worldwide, leaving many concerned about the future of their careers. [7] However, AI works best with, not instead of, humans. This means leaders have an opportunity to develop teams that excel by collaborating with AI.

Building a Culture That Embraces AI

As an AI-ready leader, your next step will be to help the rest of your organization embrace AI, too. Take these steps to develop a safe, future-proofed AI culture.

• Foster psychological safety for people to experiment: explain that new AI processes are unlikely to be efficient right away. Normalize the concept of “failing,” explaining that the team needs to test and identify what doesn’t work as much as what does.
• Recognize and reward curiosity: create incentives that encourage team members’ AI experimentation to develop new skills or applications. It may also be helpful to host showcases where different departments demonstrate their AI systems and findings.
• Redesign roles and workflows: emphasize that AI will update job roles and workflows, not necessarily replace them. From here, encourage team members to assess where AI should complement human skills and where new skills are necessary. Employees may also like to reimagine their roles using AI tools to suggest the training they need.

Practical Actions Senior Leaders Can Take Today

As an AI-ready leader with an AI-ready organization, you can employ strategies to develop innovation and growth. These five practical steps can help you get started.

1. Identify small, high-impact use cases for AI: choose the pain points where AI could offer the most immediate support. If in doubt, select the use cases that currently take up the most time, will be easiest to measure ROI, or where competitors are already seeing success.
2. Run a pilot and capture learnings: wherever you trial AI, test the application in a controlled environment to begin with. Collate data on productivity, costs and quality, and iterate based on the findings. Consider setting KPIs or success metrics, such as time saved, error reduction, or improved customer satisfaction. As the system improves, document technical lessons and create internal case studies to inspire other departments.
3. Discuss at the executive level: communicate with other departments to decide where AI should be a priority. Collaborate to prevent duplicate or conflicting AI efforts and share cross-functional learnings across the organization.
4. Partner with learning and development to help teams upskill and experiment: create role-specific training to help employees organization-wide flourish when using AI. Mentorship opportunities that pair those already in tech-focused roles with others may also be helpful.
5. Regularly review emerging tools and trends: establish a process for the organization to stay abreast of potential AI capabilities. This may involve strengthening relationships with AI experts, allocating time in meetings to discuss opportunities, and benchmarking AI adoption against industry leaders. Consider setting up a “tech radar” role in your leadership team, to scan emerging tools and filter what’s relevant to your strategy.

Who's Using AI Now Successfully

Numerous organizations are leveraging AI to develop market-leading products, offer exceptional customer service, and maximize sales. Here are three case studies spotlighting companies that are taking the lead in AI applications.

Click on the examples below to explore them:

Salesforce, a major U.S.-based cutomer relationship management company, identified an opportunity to develop an AI product that would prove transformative for customers.

They created "Agentforce," which allows users to create and launch virtual agents. These agents manage complicated tasks across workflows, from optimizing marketing campaigns to qualifying sales leads.

Salesforce has seen a case resolution increase of over 40 percent with Agentforce. [8]

Coffee colossus Starbucks developed its “Deep Brew” initiative to personalize customer interactions, optimize store labor, and manage inventory.

When developing the system, Starbucks iterated in various ways: integrating new technologies, adapting these to accommodate different markets and consumer behaviors, and investing in infrastructure and employee training.

Deep Brew saw Starbucks achieve record quarterly earnings, and it may now open doors to higher wages for baristas. [9]

Unilever collects data from 100,000 AI-enabled freezers to understand how much ice cream they are going to sell and how to process orders efficiently.

The AI responds to changing weather patterns to predict ice cream demand on a country-by-country basis. In Sweden alone, forecast accuracy has improved by 10 percent thanks to this approach.

Unilever’s forecasting system has allowed the company to boost retail orders and sales by up to 30 percent and save up to 10 percent on some raw materials. [10]

The Future Belongs to the Curious

As AI continues to develop, the leaders who embrace it will shape the future of their industries.

This may sound like an overwhelming journey to take, but you can start where you are. Stay open, strategic and human as you consider the following prompts:

• How can you build more AI readiness into your leadership?
• What small AI experiment could you lead in your area this quarter?

As you consider these questions, know that you don’t need to make the biggest financial investments to get the most out of AI. Smart, purposeful choices can be very effective.

Frequently Asked Questions

Can I start using AI if I don’t have a technical background?

You don’t need to be a techno whizz! Begin by identifying one or two high-impact, repetitive tasks in your area where AI might help. Collaborate with tech or data teams to explore options and run small pilots.

What’s the biggest risk of using AI too quickly?

Rushing implementation without testing can increase workloads, frustrate teams, or introduce ethical risks. Instead, iterate, review results, and adjust before scaling, and always involve your people in the process.

How do I balance innovation with responsibility when adopting AI?

Develop clear guardrails around data privacy, transparency, and fairness. Train teams to spot ethical issues, and ensure human oversight is built into AI decision-making processes.

What if my team is anxious about AI replacing their jobs?

Reassure them that AI is here to enhance, not replace, their work. Redesign roles collaboratively, highlight how AI can reduce mundane tasks, and provide upskilling opportunities so they feel equipped, not excluded.